Assessment of the relationships between myocardial contractility and infarct tissue revealed by serial magnetic resonance imaging in patients with acute myocardial infarction

Imaging changes in left ventricular (LV) volumes during the cardiac cycle and LV ejection fraction do not provide information on regional contractility. Displacement ENcoding with Stimulated Echoes (DENSE) is a strain-encoded cardiac magnetic resonance (CMR) technique that measures strain directly. We investigated the relationships between strain revealed by DENSE and the presence and extent of infarction in patients with recent myocardial infarction (MI). 50 male subjects were invited to undergo serial CMR within 7 days of MI (baseline) and after 6 months (follow-up; n = 47). DENSE and late gadolinium enhancement (LGE) images were acquired to enable localised regional quantification of peak circumferential strain (Ecc) and the extent of infarction, respectively. We assessed: (1) receiver operating characteristic (ROC) analysis for the classification of LGE, (2) strain differences according to LGE status (remote, adjacent, infarcted) and (3) changes in strain revealed between baseline and follow-up. 300 and 258 myocardial segments were available for analysis at baseline and follow-up respectively. LGE was present in 130/300 (43 %) and 97/258 (38 %) segments, respectively. ROC analysis revealed moderately high values for peak Ecc at baseline [threshold 12.8 %; area-under-curve (AUC) 0.88, sensitivity 84 %, specificity 78 %] and at follow-up (threshold 15.8 %; AUC 0.76, sensitivity 85 %, specificity 64 %). Differences were observed between remote, adjacent and infarcted segments. Between baseline and follow-up, increases in peak Ecc were observed in infarcted segments (median difference of 5.6 %) and in adjacent segments (1.5 %). Peak Ecc at baseline was indicative of the change in LGE status between baseline and follow-up. Strain-encoded CMR with DENSE has the potential to provide clinically useful information on contractility and its recovery over time in patients with MI

Analytical method to measure three-dimensional strain patterns in the left ventricle from single slice displacement data

Background: Displacement encoded Cardiovascular MR (CMR) can provide high spatial resolution measurements of three-dimensional (3D) Lagrangian displacement. Spatial gradients of the Lagrangian displacement field are used to measure regional myocardial strain. In general, adjacent parallel slices are needed in order to calculate the spatial gradient in the through-slice direction. This necessitates the acquisition of additional data and prolongs the scan time. The goal of this study is to define an analytic solution that supports the reconstruction of the out-of-plane components of the Lagrangian strain tensor in addition to the in-plane components from a single-slice displacement CMR dataset with high spatio-temporal resolution. The technique assumes incompressibility of the myocardium as a physical constraint. Results: The feasibility of the method is demonstrated in a healthy human subject and the results are compared to those of other studies. The proposed method was validated with simulated data and strain estimates from experimentally measured DENSE data, which were compared to the strain calculation from a conventional two-slice acquisition. Conclusion: This analytical method reduces the need to acquire data from adjacent slices when calculating regional Lagrangian strains and can effectively reduce the long scan time by a factor of two

3D cine DENSE MRI: ventricular segmentation and myocardial stratin analysis

Includes abstract. Includes bibliographical references

Noninvasive Cardiac Flow Assessment Using High Speed Magnetic Resonance Fluid Motion Tracking

Cardiovascular diseases can be diagnosed by assessing abnormal flow behavior in the heart. We introduce, for the first time, a magnetic resonance imaging-based diagnostic that produces sectional flow maps of cardiac chambers, and presents cardiac analysis based on the flow information. Using steady-state free precession magnetic resonance images of blood, we demonstrate intensity contrast between asynchronous and synchronous proton spins. Turbulent blood flow in cardiac chambers contains asynchronous blood proton spins whose concentration affects the signal intensities that are registered onto the magnetic resonance images. Application of intensity flow tracking based on their non-uniform signal concentrations provides a flow field map of the blood motion. We verify this theory in a patient with an atrial septal defect whose chamber blood flow vortices vary in speed of rotation before and after septal occlusion. Based on the measurement of cardiac flow vorticity in our implementation, we establish a relationship between atrial vorticity and septal defect. The developed system has the potential to be used as a prognostic and investigative tool for assessment of cardiac abnormalities, and can be exploited in parallel to examining myocardial defects using steady-state free precession magnetic resonance images of the heart

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival

Acceleration of tissue phase mapping with sensitivity encoding at 3T

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to investigate the impact of sensitivity encoding on the quantitative assessment of cardiac motion in black blood cine tissue phase mapping (TPM) sequences. Up to now whole volume coverage of the heart is still limited by the long acquisition times. Therefore, a significant increase in imaging speed without deterioration of quantitative motion information is indispensable.</p> <p>Methods</p> <p>20 volunteers were enrolled in this study. Each volunteer underwent myocardial short-axis TPM scans with different SENSE acceleration factors. The influence of SENSE acceleration on the measured motion curves was investigated.</p> <p>Results</p> <p>It is demonstrated that all TPM sequences with SENSE acceleration have only minimum influence on the motion curves. Even with a SENSE factor of four, the decrease in the amplitude of the motion curve was less than 3%. No significant difference was observed for the global correlation coefficient and deviation between the motion curves obtained by the reproducibility and the SENSE accelerated measurements.</p> <p>Conclusions</p> <p>It is feasible to accelerate myocardial TPM measurements with SENSE factors up to 4 without losing substantial information of the motion pattern.</p

Mapping right ventricular myocardial mechanics using 3D cine DENSE cardiovascular magnetic resonance

<p>Abstract</p> <p>Background</p> <p>The mechanics of the right ventricle (RV) are not well understood as studies of the RV have been limited. This is, in part, due to the RV's thin wall, asymmetric geometry and irregular motion. However, the RV plays an important role in cardiovascular function. This study aims to describe the complex mechanics of the healthy RV using three dimensional (3D) cine displacement encoding with stimulated echoes (DENSE) cardiovascular magnetic resonance (CMR).</p> <p>Methods</p> <p>Whole heart 3D cine DENSE data were acquired from five healthy volunteers. Tailored post-processing algorithms for RV mid-wall tissue tracking and strain estimation are presented. A method for sub-dividing the RV into four regions according to anatomical land marks is proposed, and the temporal evolution of strain was assessed in these regions.</p> <p>Results</p> <p>The 3D cine DENSE tissue tracking methods successfully capture the motion and deformation of the RV at a high spatial resolution in all volunteers. The regional Lagrangian peak surface strain and time to peak values correspond with previous studies using myocardial tagging, DENSE and strain encoded CMR. The inflow region consistently displays lower peak strains than the apical and outflow regions, and the time to peak strains suggest RV mechanical activation in the following order: inflow, outflow, mid, then apex.</p> <p>Conclusions</p> <p>Model-free techniques have been developed to study the myocardial mechanics of the RV at a high spatial resolution using 3D cine DENSE CMR. The consistency of the regional RV strain patterns across healthy subjects is encouraging and the techniques may have clinical utility in assessing disrupted RV mechanics in the diseased heart.</p